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Title: Electromagnetic ray-tracing for the investigation of multipath and vibration signatures in radar imagery
Author: Muff, Darren G.
ISNI:       0000 0004 7429 1680
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Synthetic Aperture Radar (SAR) imagery has been used extensively within UK Defence and Intelligence for many years. Despite this, the exploitation of SAR imagery is still challenging to the inexperienced imagery analyst as the non-literal image provided for exploitation requires careful consideration of the imaging geometry, the target being imaged and the physics of radar interactions with objects. It is therefore not surprising to note that in 2017 the most useful tool available to a radar imagery analyst is a contextual optical image of the same area. This body of work presents a way to address this by adopting recent advances in radar signal processing and computational geometry to develop a SAR simulator called SARCASTIC (SAR Ray-Caster for the Intelligence Community) that can rapidly render a scene with the precise collection geometry of an image being exploited. The work provides a detailed derivation of the simulator from first principals. It is then validated against a range of real-world SAR collection systems. The work shows that such a simulator can provide an analyst with the necessary tools to extract intelligence from a collection that is unavailable to a conventional imaging system. The thesis then describes a new technique that allows a vibrating target to be detected within a SAR collection. The simulator is used to predict a unique scattering signature - described as a one-sided paired echo. Finally an experiment is described that was performed by Cranfield University to specifications determined by SARCASTIC which show that the unique radar signature can actually occur within a SAR collection.
Supervisor: Griffiths, H. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available